This chapter describes about a new technology for the identification of microbes and molecular identification of drug resistance using a platform known commercially as the Ibis T5000 universal biosensor. The PCR/electrospray ionization-mass spectrometry (ESI-MS) technique was initially developed for the identification of microbes, including previously unknown or unculturable organisms, in original patient specimens or environmental surveillance samples in which multiple microbes may be present. Applications of Ibis T5000 technology can be thought of in an hourglass model. Drug resistance in bacteria and viruses is often mediated by mutations in the genes that encode the proteins that are the targets of the drugs. Many of the most important drug-microbe combinations are of this nature. An important feature of PCR/ESI-MS for detecting emerging drug resistance is that nucleic acid does not need to be isolated from pure colonies of the target microbe. The ability of PCR/ESI-MS to detect a low-abundance nucleic acid amplicon that has a mutation representing an emerging antimicrobial resistance in the presence of a higher-abundance wild-type background is critical to a number of applications. The final eight-primer-pair panel includes two primer pairs that target efp, the gene found to be the most useful in discriminating between different Acinetobacter species by MLST. Generally, drug resistance mutations in HIV arise due to selective pressure in patients with incompletely suppressed virus replication. HIV-1 isolates with drug resistance mutations may also be transmitted to newly infected individuals.

Hourglass model for applications of PCR/ESI-MS. In broad surveillance mode (top of hourglass), the technology can be used to answer the question, “What organisms are in my sample?” The center point is identification of the species, which is where most molecular methods are focused. The lower portion of the hourglass symbolizes high-resolution characterization of the genome. By using PCR/ESI-MS, species-specific primers yield high-resolution details that distinguish strain types, identify virulence and drug resistance markers, and identify emerging drug resistance.

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FIGURE 2

Hourglass model for applications of PCR/ESI-MS. In broad surveillance mode (top of hourglass), the technology can be used to answer the question, “What organisms are in my sample?” The center point is identification of the species, which is where most molecular methods are focused. The lower portion of the hourglass symbolizes high-resolution characterization of the genome. By using PCR/ESI-MS, species-specific primers yield high-resolution details that distinguish strain types, identify virulence and drug resistance markers, and identify emerging drug resistance.

Flow scheme for PCR/ESI-MS genotyping of S. aureus. DNAs from isolates or original patient specimens are distributed into eight wells of a microtiter plate, each containing a pair of primers targeted to one of the housekeeping genes analyzed in MLST. Twelve samples are analyzed per plate. Following PCR amplification and a desalting step, the amplicons are injected into an ESI-MS. The mass of the amplicons is determined with sufficient accuracy that the base composition—the A, G, C, and T counts—for the intact amplicon can be calculated. Clonal complex groupings and USA type matching are determined by comparison with a database of calculated A, G, C, and T counts derived from the sequences in the MLST database and assigned clonal complexes and USA types.

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FIGURE 3

Flow scheme for PCR/ESI-MS genotyping of S. aureus. DNAs from isolates or original patient specimens are distributed into eight wells of a microtiter plate, each containing a pair of primers targeted to one of the housekeeping genes analyzed in MLST. Twelve samples are analyzed per plate. Following PCR amplification and a desalting step, the amplicons are injected into an ESI-MS. The mass of the amplicons is determined with sufficient accuracy that the base composition—the A, G, C, and T counts—for the intact amplicon can be calculated. Clonal complex groupings and USA type matching are determined by comparison with a database of calculated A, G, C, and T counts derived from the sequences in the MLST database and assigned clonal complexes and USA types.

Priming strategy for the determination of quinolone resistance in Acinetobacter baumannii. For both gyrA and parC, primer pairs (arrows) were designed to cover the QRDR in a tiling fashion. Boxes highlight the positions of the most critical codons in Ser 83 (gyrA) or Ser80 (parC) that are covered by three primer pairs. The detected mutations are reported below the wild-type sequence.

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FIGURE 5

Priming strategy for the determination of quinolone resistance in Acinetobacter baumannii. For both gyrA and parC, primer pairs (arrows) were designed to cover the QRDR in a tiling fashion. Boxes highlight the positions of the most critical codons in Ser 83 (gyrA) or Ser80 (parC) that are covered by three primer pairs. The detected mutations are reported below the wild-type sequence.

Analysis of direct wound sample and wound culture isolates by PCR/ESI-MS. (A) Results of analysis using the Staphylococcus characterization kit of the direct wound sample (first row) and isolated colonies. (B) Mass spectra of amplicons from the gyrA gene from the direct wound sample and individual quinolone-resistant and quinolone-susceptible colonies.

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FIGURE 6

Analysis of direct wound sample and wound culture isolates by PCR/ESI-MS. (A) Results of analysis using the Staphylococcus characterization kit of the direct wound sample (first row) and isolated colonies. (B) Mass spectra of amplicons from the gyrA gene from the direct wound sample and individual quinolone-resistant and quinolone-susceptible colonies.

Analysis of plasma samples containing wild-type and mutant HIV. Eleven samples, containing 0, 0.01, 0.1, 0.5, 1, 2, 5, 10, 25, 50, and 100% mutant (at codon 103) to wild-type nucleic acid, were sampled by PCR/ESI-MS. Viral mixtures were prepared in HIV-seronegative plasma with virus stocks prepared from plasmid clones. Viral RNA was extracted and converted to noninfectious cDNA prior to PCR. The ratios of samples were blinded to our scientists until after results were generated. PCR primers previously selected to amplify the region bracketing codon 103 of the reverse transcriptase (11) were used for the T5000 analysis (forward, 5′-TGAATACCACATCCCGCAGGGTTAAAAAAG-3′, and reverse, 5′-TCACCCACATCCAGTACTGTTACTGATTT-3′). Eight PCRs were performed for each of the 11 samples in 40-μl volumes containing 10 mM Tris-Cl, 50 mM KCl, 1.5 mM MgCl2, 400 mM betaine, 4 U/reaction AmpliTaq Gold (ABI), 200 μM each dinucleoside triphosphate, and 250 nM each primer. Thermocycling consisted of 96°C for 10 min, followed by 40 cycles of 96°C for 20 s, 55°C for 45 s, 72°C for 15 s, and then 72°C for 4 min. Two independent PCR amplifications were performed on two different days. PCR product masses for each sample were measured, using ESI-time of flight-MS as described previously (7). Each mass spectrum included two peptide-based internal mass calibrants bracketing the most informative region of spectral amplitude between m/z 726 and 1,346. The raw mass spectra for each of the eight replicates for each sample were baseline subtracted and precisely calibrated along the m/z axis using Matlab-based signal processing code from the gen x MS analysis package (8). Noise-subtracted, calibrated spectra were coadded by using Matlab to increase detection sensitivity at lower input ratios. Approximate signal intensities were estimated as the sum of peak intensities for forward and reverse product strands over five specific m/z positions for each amplicon, corresponding to five independent molecular charge states. For each peak, the average signal amplitude at the interpeak interval m/z 946.22 to 946.42 was subtracted to avoid overestimating the lower-abundance peaks due to baseline elevation near the shoulders of the larger peak. (A) Representative example of signals for one charge state (CS-18) for the mutant and wild-type (wt) amplicons for each of the 11 samples at various mutant-to-wt ratios. Estimated input ratios based upon signal output ratios were calculated as [Σ(mutant)/(Σ(mutant) + Σ(wt)] * 100, where mutant and wt refer to the peak intensities of the five independent charge states examined. (B) Known and experimentally determined mutant-to-wt ratios. Upon unblinding the data, the ratio estimates were ordered by known input ratios for comparison to estimates based on output ratios. There was less than twofold variation between known and experimentally determined ratios. Detection of the lower-abundance species was unreliable below 2%.

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FIGURE 7

Analysis of plasma samples containing wild-type and mutant HIV. Eleven samples, containing 0, 0.01, 0.1, 0.5, 1, 2, 5, 10, 25, 50, and 100% mutant (at codon 103) to wild-type nucleic acid, were sampled by PCR/ESI-MS. Viral mixtures were prepared in HIV-seronegative plasma with virus stocks prepared from plasmid clones. Viral RNA was extracted and converted to noninfectious cDNA prior to PCR. The ratios of samples were blinded to our scientists until after results were generated. PCR primers previously selected to amplify the region bracketing codon 103 of the reverse transcriptase (11) were used for the T5000 analysis (forward, 5′-TGAATACCACATCCCGCAGGGTTAAAAAAG-3′, and reverse, 5′-TCACCCACATCCAGTACTGTTACTGATTT-3′). Eight PCRs were performed for each of the 11 samples in 40-μl volumes containing 10 mM Tris-Cl, 50 mM KCl, 1.5 mM MgCl2, 400 mM betaine, 4 U/reaction AmpliTaq Gold (ABI), 200 μM each dinucleoside triphosphate, and 250 nM each primer. Thermocycling consisted of 96°C for 10 min, followed by 40 cycles of 96°C for 20 s, 55°C for 45 s, 72°C for 15 s, and then 72°C for 4 min. Two independent PCR amplifications were performed on two different days. PCR product masses for each sample were measured, using ESI-time of flight-MS as described previously (7). Each mass spectrum included two peptide-based internal mass calibrants bracketing the most informative region of spectral amplitude between m/z 726 and 1,346. The raw mass spectra for each of the eight replicates for each sample were baseline subtracted and precisely calibrated along the m/z axis using Matlab-based signal processing code from the gen x MS analysis package (8). Noise-subtracted, calibrated spectra were coadded by using Matlab to increase detection sensitivity at lower input ratios. Approximate signal intensities were estimated as the sum of peak intensities for forward and reverse product strands over five specific m/z positions for each amplicon, corresponding to five independent molecular charge states. For each peak, the average signal amplitude at the interpeak interval m/z 946.22 to 946.42 was subtracted to avoid overestimating the lower-abundance peaks due to baseline elevation near the shoulders of the larger peak. (A) Representative example of signals for one charge state (CS-18) for the mutant and wild-type (wt) amplicons for each of the 11 samples at various mutant-to-wt ratios. Estimated input ratios based upon signal output ratios were calculated as [Σ(mutant)/(Σ(mutant) + Σ(wt)] * 100, where mutant and wt refer to the peak intensities of the five independent charge states examined. (B) Known and experimentally determined mutant-to-wt ratios. Upon unblinding the data, the ratio estimates were ordered by known input ratios for comparison to estimates based on output ratios. There was less than twofold variation between known and experimentally determined ratios. Detection of the lower-abundance species was unreliable below 2%.

Analysis of viral populations. Representations of mass spectral data of influenza virus amplicons generated by reverse transcriptase PCR of patient samples processed as described previously (13). The heat maps in the top sections are a charge state representation of the data; the spectral plots in the lower sections were created by filtering the charge state responses to create signal representations versus mass. The main peaks on the spectral plots correspond to amplicons from the majority species; the peaks due to amplicons from the minor species appear as “cloudy” regions to the right and left of the forward and reverse strands, respectively. The main peaks in panels A and B are due to the strain type most commonly observed in the 2005-2006 flu season. The minor peaks are due to strains with a single mutation. In panel A, the mutation is within the M1 amplicon, whereas in panel B, the point mutation is within the overlapping NS1 and NS2 amplicons.

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FIGURE 8

Analysis of viral populations. Representations of mass spectral data of influenza virus amplicons generated by reverse transcriptase PCR of patient samples processed as described previously (13). The heat maps in the top sections are a charge state representation of the data; the spectral plots in the lower sections were created by filtering the charge state responses to create signal representations versus mass. The main peaks on the spectral plots correspond to amplicons from the majority species; the peaks due to amplicons from the minor species appear as “cloudy” regions to the right and left of the forward and reverse strands, respectively. The main peaks in panels A and B are due to the strain type most commonly observed in the 2005-2006 flu season. The minor peaks are due to strains with a single mutation. In panel A, the mutation is within the M1 amplicon, whereas in panel B, the point mutation is within the overlapping NS1 and NS2 amplicons.